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Comparing Linear Discriminant Function with Logistic Regression for the Two-Group Classification Problem

Xitao Fan and Lin Wang
The Journal of Experimental Education
Vol. 67, No. 3 (Spring, 1999), pp. 265-286
Published by: Taylor & Francis, Ltd.
Stable URL: http://www.jstor.org/stable/20152599
Page Count: 22
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Comparing Linear Discriminant Function with Logistic Regression for the Two-Group Classification Problem
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Abstract

The performances of predictive discriminant analysis (PDA) and logistic regression (LR) for the 2-group classification problem were compared. The authors used a fully crossed 3-factor experimental design (sample size, group proportions, and equal or unequal covariance matrices) and 2 data patterns. When the 2 groups had equal covariance matrices, PDA and LR performed comparably for the conditions of both equal and unequal group proportions. When the 2 groups had unequal covariance matrices (4:1, as implemented in this study) and very different group proportions, PDA and LR differed somewhat with regard to the classification error rates of the 2 groups, but the classification error rates of the 2 methods for the total sample remained comparable. Sample size played a relatively minor role in the classification accuracy of the 2 methods, except when LR was used under relatively small sample-size conditions.

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